Truth Finding from Multiple Data Sources by Source Confidence Estimation

摘要：

　　The volume of data on the Web has been growing at a dramatic pace in recent years and people rely more and more on the Web to fulfill their information needs.Numerous different descriptions of the properties towards the same objects can be obtained from a variety of data sources.This will inevitably lead to data incompleteness, data conflicts and out-of-date information problems.These issues make truth discovery among multiple data sources non-trivial.However, most of previous works consider only one single property, or deal with different properties separately by ignoring several characteristics of the properties, which will often cause unexpected deviations.In this paper, we propose a modified method to find the most trustable source and identify the true information.Our goal is to minimize the distance between the true information and the overall observed descriptions through considering the accuracy and the coverage of all the data sources at the same time.The experiments on the real dataset demonstrate the efficacy of our method.

关键词： data fusion truth discovery source selection

作者: Fan Zhang Li Yu Xiangrui Cai Ying Zhang Haiwei Zhang

作者单位: College of Software, Nankai University College of Computer and Control Engineering, Nankai University College of Software, Nankai University;College of Computer and Control Engineering, Nankai Universit

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 153-156

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）